1. Field of the Invention
The invention relates to the field of grading, characterizing or processing food, fruit or produce using optical methods and apparatus.
2. Description of the Prior Art
In U.S. Pat. No. 6,958,815 we disclosed a wide field, broadband, spatially modulated illumination of turbid media, incorporated herein by reference. This approach has potential for simultaneous surface and sub-surface mapping of media structure, function and composition. This method can be applied with no contact to the medium over a large area, and could be used in a variety of applications that require wide-field image characterization. The method was refined in U.S. patent application Ser. No. 11/336,065, incorporated herein by reference, directed to an improvement in a method for quantitative modulated imaging to perform depth sectioned reflectance or transmission imaging in a turbid medium, including the steps of encoding periodic pattern of illumination preferably with a fluorescent excitation wavelength when exposing a turbid medium to the periodic pattern to provide depth-resolved discrimination of structures within the turbid medium; and reconstructing a non-contact three dimensional image of the structure within a turbid medium.
Quality assurance is one of the most important goals in any field especially in the biomedical and agricultural field. Biomedical and agricultural technologies have many things in common since plant tissue has many similar components to animal tissue. In the biomedical and agricultural fields, quality assurance involves inspection, detection, and sorting. In the fruit industry, damage and defects reduce the market value of fruits and can cause significant economic loss. One defect having considerable negative impact in the fruit industry is bruising, particularly in the apple industry. In the worldwide fruit and vegetable industries, the reduction of bruising can provide the annual payback in the billions of dollars. The bruise is a consequence of a physical and/or chemical change, which can alter the color, flavor, and texture of the fruit and may be a result of external forces that occur during harvest, transportation, or handling. The detection of bruising in apples is a difficult task because the skin often obscures the appearance of underlying damage. In addition, the detection sensitivity is dependent on apple variety, time of bruise, harvest conditions, bruise type and severity.
Manual inspection of bruises is expensive, slow, and prone to error and inconsistency. Automated machine vision systems are needed to improve the inspection process. Machine vision systems are available for performing rapid, non-destructive quick scanning of the entire surface area of the fruit. These systems are being used for sorting by size, shape, and color; but defect detection such as bruise detection remains a challenge.
A limitation of these systems is that they typically operate in simple reflectance geometry and do not quantitatively distinguish between scattering and absorption effects. Structural and chemical information, while present in the recorded signals, is typically not provided in a detailed sense. Light penetration in multiple scattering media such as fruit, both scattering and absorption contribute to the distance-dependent attenuation. Light absorption is related to chemical components in fruit, including chlorophyll, sugar, and water. On the other hand, scattering is related to the physical structure of fruit, such as cell structure. Therefore, changes in scattering should correlate with changes in physical properties of fruit such as bruising. Machine vision systems that are able to distinguish absorption and scattering in a single measurement have the potential to provide an improved quantitative assessment of fruit. A number of single point near-infrared (NIR) systems have been developed to separate absorption and scattering in turbid biological materials, which can be classified as time-domain, frequency-domain, and steady-state spatial domain. In addition, some single point spectroscopic NIR measurements have been carried out in the time domain that enables separation and quantification of optical properties of fruit. However, single point techniques are generally limited in their ability to characterize volume spatial variability of fruit, and non-optical measurements on some fruits have demonstrated variation in properties such as sugar and acid content from one side to the other side. In addition, single point measurements are limited in characterizing spatial variable surface defects and contaminations such as bruises, side rots, flyspecks, molds, and fungal diseases on apples. Machine vision systems that can separate absorption and scattering over a large area of the fruit with a single measurement will enable a more comprehensive assessment of the condition of the fruit.
Spatial Frequency Domain Imaging (SFDI) is a non-contact optical imaging technology under development for various biomedical applications including skin cancer, and port wine stain characterization, and brain imaging. Compared to other imaging approaches, SFDI has the unique capability of enabling rapid, wide-field quantitative mapping of optical properties within a single measurement platform. While compatible with time-modulation methods, SFDI uses spatially-modulated illumination for imaging of turbid sample constituents. Spatially resolved absorption and scattering coefficients are subsequently deduced using an appropriate model of light propagation. Golden Delicious apples are particularly vulnerable to bruising.